Google Reveals Flawed Assumption Driving AI Overviews' Inaccuracies
The flawed assumption causing Google's now infamous AI inaccuracies and hallucinations (eat glue, eat rocks, etc) is that Google believed its algorithm would prioritize accurate results over the spam and disinformation now flooding its search engine.
That proved to be wishful thinking, probably insisted upon by FOMO-obsessed senior executives anxious to get Google's entry out there so it could start raking in revenue and would not lose out to others. It turned out to be a prime example of an otherwise smart company blinded by its own hype. JL
Benj Edwards reports in ars technica:
The fundamental flaw of the system is that "AI Overviews are built to
only show information that is backed up by top web results." The design
is based on the false assumption that Google's page-ranking algorithm
favors accurate results and not SEO-gamed garbage. Google Searchhas been brokenforsome time, and now the company is relying on those gamed and spam-filled results to feed its new AI model. Google's AI language model can make inaccurate conclusions about "accurate" data, confabulatingerroneous information in a flawed summary of the information available.
On Thursday, Google capped off a rough week of providinginaccurate and sometimes dangerousanswers through its experimental AI Overview feature by authoring a follow-upblog posttitled,
"AI Overviews: About last week." In the post, attributed to Google VP
Liz Reid, head of Google Search, the firm formally acknowledged issues
with the feature and outlined steps taken to improve a system that
appears flawed by design, even if it doesn't realize it is admitting it.
To recap, the AI Overview feature—whichthe company showed offat
Google I/O a few weeks ago—aims to provide search users with summarized
answers to questions by using an AI model integrated with Google's web
ranking systems. Right now, it's an experimental feature that is not
active for everyone, but when a participating user searches for a topic,
they might see an AI-generated answer at the top of the results, pulled
from highly ranked web content and summarized by an AI model.
While Google claims this approach is "highly effective" and on par with itsFeatured Snippetsin
terms of accuracy, the past week has seen numerous examples of the AI
system generating bizarre, incorrect, or even potentially harmful
responses, as we detailed in arecent featurewhere Ars reporter Kyle Orland replicated many of the unusual outputs.
Drawing inaccurate conclusions from the web
Enlarge/On
Wednesday morning, Google's AI Overview was erroneously telling us the
Sony PlayStation and Sega Saturn were available in 1993.
Kyle Orland / Google
Given
the circulating AI Overview examples, Google almost apologizes in the
post and says, "We hold ourselves to a high standard, as do our users,
so we expect and appreciate the feedback, and take it seriously." But
Reid, in an attempt to justify the errors, then goes into some very
revealing detail about why AI Overviews provides erroneous information:
AI
Overviews work very differently than chatbots and other LLM products
that people may have tried out. They’re not simply generating an output
based on training data. While AI Overviews are powered by a customized
language model, the model is integrated with our core web ranking
systems and designed to carry out traditional “search” tasks, like
identifying relevant, high-quality results from our index. That’s why AI
Overviews don’t just provide text output, but include relevant links so
people can explore further. Because accuracy is paramount in Search, AI
Overviews are built to only show information that is backed up by top
web results.
This means that AI Overviews generally don't “hallucinate” or make things up in the ways that other LLM products might.
Here
we see the fundamental flaw of the system: "AI Overviews are built to
only show information that is backed up by top web results." The design
is based on the false assumption that Google's page-ranking algorithm
favors accurate results and not SEO-gamed garbage. Google Searchhas been brokenforsome time, and now the company is relying on those gamed and spam-filled results to feed its new AI model.
Even
if the AI model draws from a more accurate source, as with the 1993
game console search seen above, Google's AI language model can still
make inaccurate conclusions about the "accurate" data,confabulatingerroneous information in a flawed summary of the information available.
Generally
ignoring the folly of basing its AI results on a broken page-ranking
algorithm, Google's blog post instead attributes the commonly circulated
errors to several other factors, including users making nonsensical
searches "aimed at producing erroneous results." Google does admit
faults with the AI model, like misinterpreting queries, misinterpreting
"a nuance of language on the web," and lacking sufficient high-quality
information on certain topics. It also suggests that some of the more
egregious examples circulating on social media are fake screenshots.
"Some
of these faked results have been obvious and silly," Reid writes.
"Others have implied that we returned dangerous results for topics like
leaving dogs in cars, smoking while pregnant, and depression. Those AI
Overviews never appeared. So we’d encourage anyone encountering these
screenshots to do a search themselves to check."
(No
doubt some of the social media examples are fake, but it's worth noting
that any attempts to replicate those early examples now will likely
fail because Google will have manually blocked the results. And it is
potentially a testament to how broken Google Search is if people
believed extreme fake examples in the first place.)
While addressing the "nonsensical searches" angle in the post, Reid uses the example search, "How many rocks should I eat each day,"
which went viral in a tweet on May 23. Reid says, "Prior to these
screenshots going viral, practically no one asked Google that question."
And since there isn't much data on the web that answers it, she says
there is a "data void" or "information gap" that was filled bysatirical contentfound
on the web, and the AI model found it and pushed it as an answer, much
like Featured Snippets might. So basically, it was working exactly as
designed.
As
a result of the bad publicity, Google claims to have made more than a
dozen technical improvements to the AI Overview system. These include
"better detection of nonsensical queries," limiting the use of
user-generated content for potentially misleading advice, additional
restrictions for sensitive topics like news and health, and manually
squelching the model on certain topics known to produce erroneous
results (i.e., filters triggered by keywords).
Perhaps
unsurprisingly, the company is forgiving itself for its failures so
far. "At the scale of the web, with billions of queries coming in every
day, there are bound to be some oddities and errors. We’ve learned a lot
over the past 25 years about how to build and maintain a high-quality
search experience, including how to learn from these errors to make
Search better for everyone."
Even
if you allow for some errors in experimental software rolled out to
millions of people, there's a problem with implied authority in the
erroneous AI Overview results. The fact remains that the technology does
not inherently provide factual accuracy but reflects the inaccuracy of
websites found in Google's page ranking with an authority that can
mislead people. You'd think tech companies would be striving to build
customer trust, but now they are building AI tools and telling usnot to trust the resultsbecause they may be wrong. Maybe that's because we are not actually the customers, but theproduct.
Perhaps
Google can work around these issues before a wider rollout of the
feature, but for now, it appears that AI Overview will likely continue
to occasionally output unusual or untrustworthy results while the
company's AI search team puts out fires as it sees them.
This article on AI inaccuracies highlights the importance of precision and expertise in content creation. It's a reminder that human oversight remains crucial. For businesses like 3D Animation Services USA, ensuring high-quality, accurate outputs can set them apart in a tech-driven world. AI is powerful, but expert touch matters!
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As a Partner and Co-Founder of Predictiv and PredictivAsia, Jon specializes in management performance and organizational effectiveness for both domestic and international clients. He is an editor and author whose works include Invisible Advantage: How Intangilbles are Driving Business Performance. Learn more...
2 comments:
This article on AI inaccuracies highlights the importance of precision and expertise in content creation. It's a reminder that human oversight remains crucial. For businesses like 3D Animation Services USA, ensuring high-quality, accurate outputs can set them apart in a tech-driven world. AI is powerful, but expert touch matters!
Luxury outdoor lights elevate the exterior of your home with elegance and sophistication. Designed with high-quality materials and stylish aesthetics, these lights provide excellent illumination while enhancing the beauty of your outdoor spaces. Ideal for gardens, patios, and pathways, they create a warm and inviting atmosphere.
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